Converting scripts into reproducible workflow research objects

Carvalho, Lucas; Belhajjame, Khalid; Medeiros, Cláudia Bauzer

doi:10.1109/escience.2016.7870887

Cited by 8 publications

(11 citation statements)

References 12 publications

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“…Burrito ( Guo & Seltzer, 2012 ) captures provenance at the operating system level and provides a user interface for documenting and annotating the provenance of non-computational processes. Carvalho, Belhajjame & Medeiros (2016) present an approach to convert scripts into reproducible Workflow Research Objects. However, it is a complex process that requires extensive involvement of scientists and curators with extensive knowledge of the workflow and script programming in every step of the conversion.…”

Section: Related Workmentioning

confidence: 99%

A collaborative semantic-based provenance management platform for reproducibility

Samuel

König‐Ries

2022

PeerJ Computer Science

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Scientific data management plays a key role in the reproducibility of scientific results. To reproduce results, not only the results but also the data and steps of scientific experiments must be made findable, accessible, interoperable, and reusable. Tracking, managing, describing, and visualizing provenance helps in the understandability, reproducibility, and reuse of experiments for the scientific community. Current systems lack a link between the data, steps, and results from the computational and non-computational processes of an experiment. Such a link, however, is vital for the reproducibility of results. We present a novel solution for the end-to-end provenance management of scientific experiments. We provide a framework, CAESAR (CollAborative Environment for Scientific Analysis with Reproducibility), which allows scientists to capture, manage, query and visualize the complete path of a scientific experiment consisting of computational and non-computational data and steps in an interoperable way. CAESAR integrates the REPRODUCE-ME provenance model, extended from existing semantic web standards, to represent the whole picture of an experiment describing the path it took from its design to its result. ProvBook, an extension for Jupyter Notebooks, is developed and integrated into CAESAR to support computational reproducibility. We have applied and evaluated our contributions to a set of scientific experiments in microscopy research projects.

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Section: Related Workmentioning

confidence: 99%

A collaborative semantic-based provenance management platform for reproducibility

Samuel

König‐Ries

2022

PeerJ Computer Science

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“…In short, we cannot understand or assess claims presented from computationally opaque processes. Scripting the computational steps is important to expose the implementation of the reasoning behind a proposed claim [34][35]. We seek to meet this standard in the Whole Tale project with the Tale specification.…”

Section: Why We Found Defining Computationalmentioning

confidence: 99%

Implementing Computational Reproducibility in the Whole Tale Environment

Chard

Gaffney

Jones

et al. 2019

Proceedings of the 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems

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We present and define a structured digital object, called a "Tale," for the dissemination and publication of computational scientific findings in the scholarly record. The Tale emerges from the NSF funded Whole Tale project (wholetale.org) which is developing a computational environment designed to capture the entire computational pipeline associated with a scientific experiment and thereby enable computational reproducibility. A Tale allows researchers to create and package code, data and information about the workflow and computational environment necessary to support, review, and recreate the computational results reported in published research. The Tale then captures the artifacts and information needed to facilitate understanding, transparency, and execution of the Tale for review and reproducibility at the time of publication.

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“…In [Carvalho et al 2016a], we state that there is a need to check the quality of the actual script-to-workflow conversion, and to assess the quality of the resulting workflow. In our solution, we adopt Quality Flow [Sousa et al 2014] to allow scientists to annotate the elements that make up the workflow with quality information.…”

Section: Quality Flowmentioning

confidence: 99%

“…Taking this overall scenario into account, we designed W2Share, a framework for retrieval and conversion of script-based experiments into executable workflows [Carvalho et al 2016b]. The script-to-workflow conversion is based on a methodology proposed by us [Carvalho et al 2016a]. Reproducibility is enabled, via this methodology, by the adoption of Workflow Research Objects (WRO) [Belhajjame et al 2015].…”

Section: Introductionmentioning

confidence: 99%

Implementing W2Share: Supporting Reproducibility and Quality Assessment in eScience

Carvalho¹,

Malaverri²,

Medeiros³

2017

Anais Do XI Brazilian E-Science Workshop (BRESCI 2017)

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An open problem in scientific community is that of supporting reproducibility and quality assessment of scientific experiments. Solutions need to be able to help scientists to reproduce experimental procedures in a reliable manner and, at the same time, to provide mechanisms for documenting the experiments to enhance integrity and transparency. Moreover, solutions need to incorporate features that allow the assessment of procedures, data used and results of those experiments. In this context, we designed W2Share, a framework to meet these requirements. This paper introduces our first implementation of W2Share, which moreover guides scientists in step-by-step process to ensure reproducibility based on a script-to-workflow conversion strategy. W2Share also incorporates features that allow annotating experiments with quality information. We validate our prototype using a real-world scenario in Bioinformatics.

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Converting scripts into reproducible workflow research objects

Cited by 8 publications

References 12 publications

A collaborative semantic-based provenance management platform for reproducibility

A collaborative semantic-based provenance management platform for reproducibility

Implementing Computational Reproducibility in the Whole Tale Environment

Implementing W2Share: Supporting Reproducibility and Quality Assessment in eScience

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